/**
* Calculates new weight for a particle.
*
* @param p Particle whose weight will be calculated
*/
private void calcWeight(Particle p) {
double weight = 0;
// list with new weights
List<Double> weight_list = new ArrayList<Double>();
List<Measure> mlist = p.getMeasure();
// measures at this location
for (int i = 0; i < current.size(); i++) {
String ssid = current.get(i).getBSSID();
// all measures from generated particle
for (int j = 0; j < mlist.size(); j++) {
String ssid_part = mlist.get(j).getBSSID();
// same ssids --> I can calculate a new weight
if (ssid.equals(ssid_part)) {
// rssi from actual location
int rssi_curr = current.get(i).getRssi();
// rssi from particle
int rssi_part = mlist.get(j).getRssi();
// calc new weight; typecast is necessary
weight = ((double) rssi_curr) / ((double) rssi_part);
// get percentage
if (weight > 1.0) weight = 1.0 / weight;
// add to list
weight_list.add(weight);
}
}
}
double sum = 0;
int number_weights = weight_list.size();
// calc sum of all weights
for (int k = 0; k < number_weights; k++) sum = sum + weight_list.get(k);
// double mean_weight = sum / number_weights;
double mean_weight = sum / current.size();
// set new weight
p.setWeight(mean_weight);
}
/** Method creates and initializes all particles. */
public void initFilter() {
// calc initial weight
double initial_weight = 1.0 / num_part;
for (int i = 0; i < num_part; i++) {
// create random point
Point p = createRandomPoint();
// new particle on point p
Particle part = new Particle(p);
// interpolate particle part by his neighbors from database
InterpolateParticle ip = new InterpolateParticle(part, db_list);
Particle clean = ip.interpolatedParticle();
// set intial weight
clean.setWeight(initial_weight);
// add particle to list
part_list.add(clean);
}
}
/**
* Creates particles on their probability-density-function. More probable particles are
* propagated. Less probable particles will be rejected and replaced by new more probable
* particles.
*/
public void propagate() {
// calcs sum of all weights
double sum = sumWeight(part_list);
// mean weight overall particles
double mean_weight = sum / num_part;
// List for particles
List<Particle> tmp_list = new ArrayList<Particle>();
double mean_x = 0;
double mean_y = 0;
for (int i = 0; i < part_list.size(); i++) {
// get particle from list
Particle p = part_list.get(i);
// weight of particle
double weight = p.getWeight();
// if particle has more weight than average particle, write to list
if (weight >= mean_weight) {
tmp_list.add(p);
// calc sum of coordinates
mean_x = mean_x + p.getX();
mean_y = mean_y + p.getY();
}
}
// calc mean coordinate
mean_x = Math.round(mean_x / tmp_list.size());
mean_y = Math.round(mean_y / tmp_list.size());
int x = (int) mean_x;
int y = (int) mean_y;
// difference between all particles and more probable particles
int diff = num_part - tmp_list.size();
// there must be a difference, except for completely degeneration
if (diff > 0) {
// initial weight
double initial_weight = 1.0 / num_part;
// create new particles according to difference
for (int j = 0; j < diff; j++) {
Point new_coord;
Particle part;
// only if there is a mean position of predicted particle
if ((x != 0) && (y != 0)) {
// new particle on pseudo-random point near predicted point
new_coord = createPseudoRandomPoint(x, y);
part = new Particle(new_coord);
} else {
// new particle on random point
new_coord = createRandomPoint();
part = new Particle(new_coord);
}
// new particle on random point
// Point new_coord = createRandomPoint();
// Particle part = new Particle(new_coord);
// interpolate from neigborhood
InterpolateParticle ip = new InterpolateParticle(part, db_list);
Particle clean = ip.interpolatedParticle();
// set new weight
clean.setWeight(initial_weight);
tmp_list.add(clean);
}
}
// update particlelist
part_list = tmp_list;
}
